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Project Point Cloud (PC)
Project PC investigates innovative methods for generating point clouds (PC) as the foundation for shapes and CAD models. Points, represented as Cartesian coordinates, are considered the "DNA" of any shape. The project focuses on practical, human-in-the-loop approaches that minimize computational burden, eliminate dependency on commercial tools, and emphasize human creativity over black-box methods. These efforts aim to simplify the creation of point clouds and facilitate their use in CAD modeling and reverse engineering.
Signal Segmentation
The Signal Segmentation App enables users to upload, visualize, and segment signal data. Version 1.0 supports a single signal file with interactive segmentation via a range slider and the ability to save the segmented portion. Version 2.0 enhances this functionality by handling three signals simultaneously, providing individual plots, shared segmentation controls, and separate save options for each signal.
Traditional Joinery
Spur Gear Design Tool
This tool generates point clouds of gear/pinion tooth profiles.
Version 4 animates a meshing pair—a gear and a pinion—with fixed parameters (including a 20° pressure angle).
In contrast, Version 5 focuses on a single gear/pinion, allowing user-defined inputs for the module, teeth, pressure angle, and scale, and adds extra visual features like addendum and dedendum circles plus a static Matplotlib plot of the point cloud.
Both versions enable users to quickly generate and analyze gear/pinion profile data for simulation or CAD integration.
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DNA-Based Computing (DBC) tool
This tool ingests a one-dimensional numerical time series. It then allows the configuration of parameters (in default, modified, or direct-input modes) and applies DNA-forming rules to translate time series data into DNA sequence(s). It constructs an mRNA from that DNA(s), following an mRNA-forming rule, and ultimately derives a protein via a built-in codon-to-amino-acid mapping (Genetic Rules) from the mRNA. The DBC tool supports exporting the final results (DNA, mRNA, Protein) in JSON format.